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Nat Med. 2019 Mar;25(3):487-495. doi: 10.1038/s41591-019-0381-y. Epub 2019 Mar 6.

A clinically meaningful metric of immune age derived from high-dimensional longitudinal monitoring.

Author information

1
Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel.
2
Institute of Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA.
3
CytoReason, Tel-Aviv, Israel.
4
Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
5
Department of Cardiology, Rambam Health Care Campus, Haifa, Israel.
6
Department of Cardiology, Bnai Zion Medical Center, Haifa, Israel.
7
Division of Pediatric Infectious Diseases, Stanford University School of Medicine, Stanford, CA, USA.
8
Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA, USA.
9
Institute of Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA. mmdavis@stanford.edu.
10
Department of Microbiology & Immunology, Stanford University School of Medicine, Stanford, CA, USA. mmdavis@stanford.edu.
11
The Howard Hughes Medical Institute, Chevy Chase, MD, USA. mmdavis@stanford.edu.
12
Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel. shenorr@technion.ac.il.

Abstract

Immune responses generally decline with age. However, the dynamics of this process at the individual level have not been characterized, hindering quantification of an individual's immune age. Here, we use multiple 'omics' technologies to capture population- and individual-level changes in the human immune system of 135 healthy adult individuals of different ages sampled longitudinally over a nine-year period. We observed high inter-individual variability in the rates of change of cellular frequencies that was dictated by their baseline values, allowing identification of steady-state levels toward which a cell subset converged and the ordered convergence of multiple cell subsets toward an older adult homeostasis. These data form a high-dimensional trajectory of immune aging (IMM-AGE) that describes a person's immune status better than chronological age. We show that the IMM-AGE score predicted all-cause mortality beyond well-established risk factors in the Framingham Heart Study, establishing its potential use in clinics for identification of patients at risk.

Comment in

PMID:
30842675
PMCID:
PMC6686855
DOI:
10.1038/s41591-019-0381-y
[Indexed for MEDLINE]
Free PMC Article

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